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Trump Tweeted. Markets Tanked. Who Sold?

By Irene Aldridge

Yesterday, on December 4, 2018, at 10:03 AM ET, President Trump has tweeted about tariffs. Shortly thereafter, the U.S. equity markets entered a significant intraday decline that many online commentators attributed directly to the President’s tweet.

While the observed market sell-off may or may not be directly related to tweet in question, it is interesting to examine which market participants actually sold off the U.S. stocks vs. which ones held on. AbleMarkets offers just such ability. By using cutting-edge Big Data techniques, AbleMarkets separates order flow into three broad categories: Institutional (think large, sophisticated pension funds and hedge funds), Aggressive HFT (prop shops and execution in banks) and Retail (all the rest) throughout the day, AbleMarkets can pinpoint the nature of the sell-off, and, therefore, predict its impact into the future. Sell-offs produced by Aggressive HFT, for example, tend to be short-lived, while those created by Institutional Activity tend to be long-lasting.

Figures 1 and 2 show the intraday Aggressive HFT and Institutional dynamics in the U.S. S&P 500 ETF (SPY) on the day of the controversial tweet by the President. As the Figures show, the institutions (Figure 2) were the first to negatively react to the President’s tweet, creating a sell-off from 10:30 AM through mid-day. During the same time, Aggressive HFTs were buying the SPY, potentially based on strictly quantitative models that did not take Trump’s tweets into account and, therefore, deemed SPY oversold. By the afternoon, however, the dynamics reversed: the institutions began to accumulate SPY on the cheap while the broad market still appeared in freefall, potentially prodded downward by readjusted AHFT. It is the institutional investors that appeared responsible for the bump in the SPY price observed from 2:30 to 3:30 PM on December 4, 2018.

Figure 1. Intraday AbleMarkets Aggressive HFT Activity Index for the S&P 500 ETF (SPY) on December 4, 2018, the day of President Trump’s “I am the Tariff Man” tweet.

Figure 2. Intraday AbleMarkets Institutional Activity Index for the S&P 500 ETF (SPY) on December 4, 2018, the day of President Trump’s “I am the Tariff Man” tweet.

Aggressive High-Frequency Trading (HFT) is a subclass of high-frequency strategies that feeds on rapidly-fleeting informational advantage (“rapidly-decaying alpha”) and volatility. As described in High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems by Aldridge (2nd edition, 2013, Wiley), unlike their passive cousins, aggressive HFTs scour the news and pounce on tradeable information, often much ahead of the broader market. As a result, not only do Aggressive HFT make the markets more efficient by impounding all available information as soon as possible, but their activity is also highly predictive of the short-term price direction. AbleMarkets estimates Aggressive HFT by tracing the AHFT footprint in the markets obtained using sophisticated Big Data techniques.

AbleMarkets measures Institutional Activity by tracing the footprints of electronic execution in the markets. Since institutional positions tend to be large and move the markets significantly, if announced, institutional managers prefer to break down their execution positions into small chunks with the explicit aim of avoiding detection by other market participants. Most institutions today deploy some kind of algorithmic trading in an attempt to avoid detection or rely on specialized exchanges and dark pools to avoid detection of their orders. While algorithms such as VWAP remain go-to standards for institutional execution, AbleMarkets research shows that they are easily detected using Big Data techniques. AbleMarkets continuously analyzes the market data in real time to pinpoint likely institutional activity in the otherwise anonymous data flow and report it to our clients.


This flow analysis is what makes it possible for AbleMarkets clients to accurately predict items like

  • the end-of-day direction of the market,
  • impending volatility (several days ahead), and even
  • price movements at the end of the month, when institutional activity typically picks up as many institutions move in and out of their positions
  • Other applications abound

To start benefiting from the AbleMarkets Institutional and Aggressive HFT Indexes today, please sign up here:

AbleMarkets products are presently available for U.S. equities, major European indexes, Top 40 currencies, major commodity futures and more.


Irene Aldridge is Managing Director of AbleMarkets, a pioneer Big Data and Machine Learning Platform for Finance. She is a co-author of Real-Time Risk: What Investors Should Know About Fintech, High-Frequency Trading and Flash Crashes (with Steve Krawciw, Wiley 2017) and author of High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems (2nd edition, Wiley 2013). She can be reached by email at